71 citations · 120 across the 9 of their papers we have counts for
9 papers
Federated Learning: Balancing the Thin Line Between Data Intelligence and Privacy
Sherin Mary Mathews, Samuel A. Assefa
Federated learning holds great promise in learning from fragmented sensitive data and has revolutionized how machine learning models are trained. This article provides a systematic…
Simulation Intelligence: Towards a New Generation of Scientific Methods
Alexander Lavin, David Krakauer, Hector Zenil +21
The original "Seven Motifs" set forth a roadmap of essential methods for the field of scientific computing, where a motif is an algorithmic method that captures a pattern of comput…
Tradeoffs in Streaming Binary Classification under Limited Inspection Resources
Parisa Hassanzadeh, Danial Dervovic, Samuel Assefa +2
Institutions are increasingly relying on machine learning models to identify and alert on abnormal events, such as fraud, cyber attacks and system failures. These alerts often need…
Non-Parametric Stochastic Sequential Assignment With Random Arrival Times
Danial Dervovic, Parisa Hassanzadeh, Samuel Assefa +1
We consider a problem wherein jobs arrive at random times and assume random values. Upon each job arrival, the decision-maker must decide immediately whether or not to accept the j…
Advising Agent for Service-Providing Live-Chat Operators
Aviram Aviv, Yaniv Oshrat, Samuel A. Assefa +4
Call centers, in which human operators attend clients using textual chat, are very common in modern e-commerce. Training enough skilled operators who are able to provide good servi…
Copula Flows for Synthetic Data Generation
Sanket Kamthe, Samuel Assefa, Marc Deisenroth
The ability to generate high-fidelity synthetic data is crucial when available (real) data is limited or where privacy and data protection standards allow only for limited use of t…
SURF: Improving classifiers in production by learning from busy and noisy end users
Joshua Lockhart, Samuel Assefa, Ayham Alajdad +3
Supervised learning classifiers inevitably make mistakes in production, perhaps mis-labeling an email, or flagging an otherwise routine transaction as fraudulent. It is vital that…
Some people aren't worth listening to: periodically retraining classifiers with feedback from a team of end users
Joshua Lockhart, Samuel Assefa, Tucker Balch +1
Document classification is ubiquitous in a business setting, but often the end users of a classifier are engaged in an ongoing feedback-retrain loop with the team that maintain it.…
On the Importance of Opponent Modeling in Auction Markets
Mahmoud Mahfouz, Angelos Filos, Cyrine Chtourou +5
The dynamics of financial markets are driven by the interactions between participants, as well as the trading mechanisms and regulatory frameworks that govern these interactions. D…